Episode Details

Cartels are unstable by nature. Members cheat, managers change, companies are sold, and participants can get away with less punishment by reporting the cartel before everybody else.

When AI encounters that familiar process, what happens next? Join us for episode 7. We start with the European MCAA cartel. Clariant acquired Hoechst’s chemicals business in 1997; the cartel continued for a while, and Clariant later discovered the conduct and reported it to the European Commission. The announcement triggered an investigation by the Commission. That history reveals a new source of cartel instability that has been overlooked: the firms may remain constant, but the people and organizations within them change.

AI complicates the narrative. If business divisions can have their pricing systems, senior management may see the results but be unaware of the strategies the systems have learned. An internal investigation may uncover substantial amounts of information but not the telltale signs of a human cartel—meetings, emails, or an explicit agreement.

In contrast, the situation is with the DOJ’s RealPage case. RealPage involved a visible common pricing system and an alleged sharing of competitors' nonpublic information. But what if every landlord had their own autonomous AI and no confidential information was shared? Would investigators be looking at an AI agreement, or just interdependence, if their prices stayed coordinated?

The law has a lot of experience distinguishing agreement from parallel behavior among humans. It has much less experience making the same sort of distinction when autonomous systems interact.

Read the full article and graphic analysis: https://blog.econworks.com/p/cartels-episode-7-why-cartels-collapseand?r=562wri

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